Sales Forecasting and Analysis for Retail Businesses

• Author(s): Kamarajugadda Sree Kalyani ; Gurram Manaswi ; Kankanala Krishna Bhavitha ; Battala Krishna Bharat
• Paper ID: 1709512
• Page: 1187-1196
• Published Date: 29-07-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 1 July-2025

Abstract

Sales forecasting and analysis are crucial in business decision-making because they allow organizations to predict future trends and streamline their strategies. The following article introduces a hybrid model which combines Facebook Prophet and XGBoost to enhance the accuracy of the sales prediction. Prophet, being a time-series forecasting tool, excels in detecting seasonality and trends, and XGBoost, a powerful machine learning algorithm, finds complex relationships and non-linear trends in sales information. The technique suggested leverages past sales transaction history to predict future revenues for the next month. The combined model houses the strengths of both worlds, with Prophet doing time-series decomposition, and XGBoost refining residual trends, ending up with more accurate forecast results. The performance is gauged with Mean Squared Error (MSE) and Mean Absolute Error (MAE to establish its accuracy). Experimental outcomes show the hybrid method exceeds the performance of individual models when forecasting accuracy and hence is an appealing solution to retail companies aiming for data-based decision-making. The hybrid model can be made to include extrinsic variables such as promotions, holidays, and economic indicators, thus further enhancing prediction performance. The above changes make the approach sufficient for dynamic retail environments where demand patterns change over time. Moreover, investigating real-time forecasting possibilities and automation can give businesses real-time insights, allowing pre-emptive decision-making and strategic planning in a competitive marketplace.

Keywords

Sales Forecasting, Hybrid Model, Prophet, Xgboost, Forecast Accuracy

Citations

IRE Journals:
Kamarajugadda Sree Kalyani , Gurram Manaswi , Kankanala Krishna Bhavitha , Battala Krishna Bharat "Sales Forecasting and Analysis for Retail Businesses" Iconic Research And Engineering Journals Volume 9 Issue 1 2025 Page 1187-1196

IEEE:
Kamarajugadda Sree Kalyani , Gurram Manaswi , Kankanala Krishna Bhavitha , Battala Krishna Bharat "Sales Forecasting and Analysis for Retail Businesses" Iconic Research And Engineering Journals, 9(1)